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AI Models and LLM Landscape

AI Models We Work With: From Cloud APIs to Self-Hosted LLMs

Plavno helps businesses pick and run the right AI model for the job — whether that means calling GPT-5.5, Claude or Gemini through an API, or deploying open-weight models like Qwen, DeepSeek and Llama on private infrastructure. We handle model benchmarking, license review, integration architecture and production operations, so your choice of model is driven by your data, budget and compliance needs — not by vendor lock-in.

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Custom GPT Integration Solutions

Develop Diverse GPT-Powered Solutions for Your Business

OpenAI Models
OpenAI Models

OpenAI Models

Frontier reasoning and coding through the OpenAI API — the default choice when raw capability and a mature ecosystem matter most.

Anthropic Claude
Anthropic Claude

Anthropic Claude

Claude models excel at complex reasoning, long documents and coding — with a safety profile that enterprise compliance teams appreciate.

  • Claude Fable 5 — Anthropic's newest frontier model

  • Opus 4.8 and Sonnet 4.6 for production loads

  • Haiku 4.5 for speed and cost efficiency

  • Agentic workflows on Claude

Google Gemini
Google Gemini

Google Gemini

Natively multimodal models that fit naturally into Google Cloud environments and media-heavy products.

  • Gemini 3.1 Pro for multimodal reasoning

  • Gemini 3.1 Flash for high-volume tasks

  • Vertex AI deployment

  • Video, image and audio understanding

More Cloud APIs: Grok, Mistral, DeepSeek
More Cloud APIs: Grok, Mistral, DeepSeek

More Cloud APIs: Grok, Mistral, DeepSeek

Beyond the big three, we integrate alternative APIs where they win on price, context length or data residency.

  • xAI Grok for real-time products

  • Mistral Large 3 for EU data residency

  • DeepSeek V4-Pro / V4-Flash for low-cost 1M context

  • Multi-provider routing and fallbacks

Qwen Model Family
Qwen Model Family

Qwen Model Family

Alibaba's open-weight lineup under Apache 2.0 — a commercially clean foundation for self-hosted products.

  • Qwen3.5-397B-A17B multimodal flagship

  • Qwen3.6-27B compact deployments

  • Qwen3-Coder-Next for coding workloads

  • Qwen-VL for vision tasks

Frontier Open-Weight: GLM, DeepSeek, Kimi, MiniMax
Frontier Open-Weight: GLM, DeepSeek, Kimi, MiniMax

Frontier Open-Weight: GLM, DeepSeek, Kimi, MiniMax

The strongest open-weight models available today — MIT and Apache licensed, with 1M-token context and frontier-level coding.

  • GLM-5.2 / GLM-5.1 all-around coding (MIT)

  • DeepSeek V4-Pro and V4-Flash (MIT)

  • Kimi K2.6 for agent swarms and long runs

  • MiniMax M3 with native multimodality

Llama and Western Open Models
Llama and Western Open Models

Llama and Western Open Models

The most widely adopted open-weight ecosystem in enterprise — we deploy it with proper license due diligence.

  • Llama 4 Maverick for general workloads

  • Llama 4 Scout with up to 10M context

  • License review (700M MAU cap, EU terms)

  • Mistral Large 3 open weights (Apache 2.0)

Small and Edge Models
Small and Edge Models

Small and Edge Models

Compact models that run on a single GPU or on-device — for latency-critical, offline and cost-sensitive scenarios.

  • Gemma 4 26B/31B for edge deployment

  • Phi-4 / Phi-4-mini for compact reasoning

  • Mistral Small 4 (24B, single GPU)

  • Nemotron 3 Super on NVIDIA stack

Eugene Katovich

Eugene Katovich

Sales Manager

Not Sure Which Model Fits? Let's Find Out Together

Model choice is a business decision, not a leaderboard contest. Plavno benchmarks candidate models on your real data and metrics, reviews licensing against your jurisdiction, and estimates total cost of ownership for API versus self-hosted setups — before you commit to an architecture. Then we build it: integration, infrastructure, monitoring and everything in between.

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Case Study

Products We've Shipped on These Models

AI Customer Success Copilot for Churn Prediction, Renewals & Account Intelligence

Plavno developed an AI customer success copilot that helps SaaS and subscription businesses detect churn risk, strengthen renewal workflows, and unify account intelligence across product, support, and customer success operations.

Read More
60–70%

reduction in manual account review work

AI Customer Success Copilot for Churn Prediction, Renewals & Account Intelligence

AI Voice Agent for Legal Intake and Client Call Handling in Law Firms

Plavno developed a Voice AI solution for law firms and AttorneyTech providers that helps automate first-line communication with prospective clients, reduce repetitive receptionist and intake work, and create a more structured legal intake process.

Read More
99.9%+

reliability targets

AI Voice Agent for Legal Intake and Client Call Handling in Law Firms

Whom We Serve

Who Benefits From Model-Agnostic AI Engineering

Enterprises With Data Residency Requirements
SaaS Teams Scaling AI Features
Startups Optimizing AI Unit Economics
Regulated Industries (Finance, Healthcare, Legal)
Products Migrating Between AI Providers
Companies Building on Open-Weight Models

Benefits

Why Model Choice Matters for Your Bottom Line

  • Lower AI Costs at Scale: routing routine tasks to compact or open-weight models while reserving frontier APIs for hard problems can cut inference spend dramatically without hurting quality.

  • No Vendor Lock-In: a model-agnostic architecture lets you switch providers as pricing, quality and terms change — and they change every quarter.

  • Data Stays Where You Need It: self-hosted open-weight models keep sensitive data on your infrastructure, simplifying compliance in regulated industries and specific jurisdictions.

  • Licensing Without Surprises: Apache 2.0 and MIT models are clean for commercial use; custom licenses like Llama's need review — we do that due diligence before you build.

  • Evidence-Based Selection: we benchmark models on your actual tasks and data rather than public leaderboards, so the model you pick performs where it counts.

<span>Why Model Choice Matters</span> for Your Bottom Line
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Paying too much for inference — or stuck with one vendor? Let's fix that.

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Security Measures

Compliance and Security Essentials

License Due Diligence

License Due Diligence

Every open-weight deployment starts with a legal check: license type, commercial terms, usage caps and jurisdiction-specific restrictions, documented before a single GPU spins up.

Private Deployment Architecture

Private Deployment Architecture

Self-hosted models run inside your network perimeter with encrypted data flows, isolated environments and no third-party data sharing.

Access and Cost Governance

Access and Cost Governance

Role-based access to models and outputs, per-team usage quotas, and spend monitoring across every provider and deployment.

Model Behavior Testing

Model Behavior Testing

We evaluate models for hallucinations, prompt injection resilience, data leakage and policy violations on your scenarios before production rollout.

Advanced Tech

The Engineering Behind Model Operations

Frequently Asked Questions

FAQs

Find answers to your common concerns

Which AI models does Plavno work with?

We work across the full landscape: cloud APIs from OpenAI (GPT-5.5, Codex, o-series), Anthropic (Claude Fable 5, Opus, Sonnet, Haiku), Google (Gemini 3.1), xAI, Mistral and DeepSeek — plus open-weight models including Qwen, GLM, DeepSeek, Kimi, MiniMax, Llama, Gemma, Phi and Nemotron.

Should we use a cloud API or a self-hosted model?

It depends on your data sensitivity, request volume and budget. APIs win on speed to market and access to frontier capability; self-hosted open-weight models win on data control, predictable costs at scale and independence from vendor terms. Many of our clients end up with a hybrid of both.

Are open-weight models good enough for production?

Yes — today's leading open-weight models deliver frontier-level coding and reasoning with up to 1M-token context. For many workloads the quality gap versus proprietary APIs has effectively closed, while the cost and privacy advantages remain.

Is it legal to build a commercial product on open-weight models?

In most cases yes. Models under Apache 2.0 or MIT (Qwen, GLM, DeepSeek, Mistral, Gemma, Phi) are clean for commercial use. Custom licenses like Meta's Llama terms include usage caps and regional restrictions — we review those against your specific case before deployment.

What infrastructure do self-hosted models require?

It varies from a single GPU for compact models like Mistral Small 4 or Phi-4 to multi-GPU clusters for large mixture-of-experts models. We size the infrastructure to your workload and can deploy on your hardware, your cloud accounts or our managed environment.

Can you migrate our product from one model to another?

Yes. We handle provider migrations end to end: prompt and output compatibility testing, quality benchmarking before and after, cost comparison, and a routing layer that lets you switch or mix providers without rewriting your product.

How do you choose which model to recommend?

We run your representative tasks through candidate models and measure quality, latency and cost per task — then factor in licensing, data residency and your team's stack. The recommendation comes with numbers, not opinions.

How much does model integration or self-hosting cost?

API integration projects depend on scope and the number of systems involved. Self-hosted deployments add infrastructure sizing and serving setup. After a short discovery we provide an estimate covering both the build and the ongoing run costs.

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Vitaly Kovalev

Vitaly Kovalev

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